CN102253048B - Machine vision detection method and system for detection of various products - Google Patents
Machine vision detection method and system for detection of various products Download PDFInfo
- Publication number
- CN102253048B CN102253048B CN 201110111714 CN201110111714A CN102253048B CN 102253048 B CN102253048 B CN 102253048B CN 201110111714 CN201110111714 CN 201110111714 CN 201110111714 A CN201110111714 A CN 201110111714A CN 102253048 B CN102253048 B CN 102253048B
- Authority
- CN
- China
- Prior art keywords
- vision
- product
- detection
- instrument
- products
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 129
- 238000000034 method Methods 0.000 claims abstract description 9
- 230000000007 visual effect Effects 0.000 claims description 16
- 230000007246 mechanism Effects 0.000 claims description 12
- 238000012360 testing method Methods 0.000 claims description 12
- 230000002950 deficient Effects 0.000 claims description 6
- 230000007547 defect Effects 0.000 claims description 3
- 230000003993 interaction Effects 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 230000004044 response Effects 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 description 5
- 238000007689 inspection Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 206010027940 Mood altered Diseases 0.000 description 1
- 230000000712 assembly Effects 0.000 description 1
- 238000000429 assembly Methods 0.000 description 1
- 238000010923 batch production Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
Images
Landscapes
- Image Analysis (AREA)
- Image Processing (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention discloses a machine vision detection method and a machine vision detection system for the detection of various products. The method comprises the following steps of: acquiring images of the products to be detected, performing feature matching of the images and prestored vision distinguishing features to find normally-measured products matched with the images, so that a machine considers that the products to be detected and the found normally-measured products are the congeneric products obviously; finding detection configuration parameters corresponding to the normally-measured products; and calling vision detection tools corresponding to the normally-measured products, loading the found detection configuration parameters, and performing vision detection on the products to be detected according to the called vision detection tools. When the machine vision detection method and the machine vision detection system are used, the models of the products can be identified automatically and intelligently, and after being identified, the products can be detected.
Description
Technical field
The present invention relates to the automatic producing technology field, be specifically related to a kind of machine vision detection method and system that multiple product detects that can be used for.
Background technology
At present, the quality inspection of the outward appearance of known bulk article and profile mainly still adopts human eye to carry out mostly, the factor such as work when tired, people can not grow in being in a bad mood, some high temperature or the toxic environment easily easily because the judgement of human eye is difficult for quantification and execution, human eye, cause present Product Visual detection generally judge by accident and false determination ratio higher.
So, mechanical vision inspection technology has obtained fast-developing and has popularized, but, existing mechanical vision inspection technology is functional single, and a kind of machine vision detection device generally can only correspondingly detect independent a kind of specific product, because in the production run, often need a plurality of assemblies of a complete product are carried out vision-based detection, this just so that the needs correspondence disposes multiple vision-based detection machine, not only wastes resource, and has reduced whole detection efficiency.
Summary of the invention
The objective of the invention is to overcome weak point of the prior art, a kind of machine vision detection method that multiple product detects that can be used for is provided.
Another object of the present invention is to provide a kind of Machine Vision Inspecting System that multiple product detects that can be used for.
The objective of the invention is to be achieved through the following technical solutions: can be used for the machine vision detection method that multiple product detects, the corresponding detection configuration parameter of the visual difference feature of pre-stored various normal survey products, various normal survey products, and the vision-based detection instrument of various normal survey products, this method specifically may further comprise the steps:
A. gather the image of product to be measured, image and pre-stored visual difference feature are carried out characteristic matching, find out the normal survey product with this images match, wherein, machine assert that described product to be measured and the normal survey product of finding out are like product;
B. find out the detection configuration parameter corresponding with normal survey product;
C. call the vision-based detection instrument corresponding with the normal survey product of finding out, and load the detection configuration parameter of finding out, then according to the vision-based detection instrument that calls product to be measured is carried out vision-based detection.
In this method, the corresponding detection configuration parameter of described various normal survey products is vision-based detection content and camera parameter setting.Wherein, the vision-based detection content specifically comprise in the having or not of outward appearance, color and principal character of various normal survey products one or more etc.Camera parameter setting specifically comprises one or more in camera resolution, time shutter and the RGB gain etc.
In this method, the vision-based detection instrument of described various normal survey products includes orientation tool, testing tool and analyzes the output instrument.Wherein, orientation tool comprises based on the orientation tool of contour feature with based on the orientation tool of unique point; Testing tool comprises dimensional measurement instrument, bar code recognition instrument, color and gray scale detection instrument, character recognition, Region Matching testing tool and profile defect detection tool; Analyze the output instrument and comprise product hierarchy decision means and I/O control tool; But similar tools parallel running, the operation of inhomogeneity instrument serializable, the vision-based detection flow process is formed by these vision-based detection tool combinations, and the parameter of the array mode of these instruments and concrete instrument is also namely carried out pre-stored as detecting configuration parameter as the vision-based detection content.
The vision-based detection tool detection go out product to be measured whether qualified after, if defective, then controlling automatic reject mechanism should reject by underproof product to be measured, defective at same problem point such as a plurality of products to be measured of continuous appearance, then automatically stops to detect and making man-machine response.
Can be used for the Machine Vision Inspecting System that multiple product detects, comprising:
The normal Product Visual distinguishing characteristics thesaurus of surveying is for the visual difference feature of the various normal survey products that prestore;
Detect the configuration parameter thesaurus, for the corresponding detection configuration parameter of the various normal survey products that prestore;
Vision-based detection instrument thesaurus is for the vision-based detection instrument of the various normal survey products that prestore;
Image acquisition units includes a plurality of cameras that multi-angle is made a video recording;
The product identification unit carries out characteristic matching for the image of the product to be measured that will gather and pre-stored visual difference feature, identifies product to be measured and surveys product for which kind of is normal;
Detection control unit according to the recognition result of product identification unit, is called corresponding vision-based detection instrument, loads the detection configuration parameter to the vision-based detection instrument from detecting the configuration parameter thesaurus, and product to be measured is carried out vision-based detection.
Camera in the described image acquisition units preferably adopts high speed linear array Charge Coupled Device (CCD) imageing sensor (CCD) camera, can analyze the sharpness of interference image and automatically be adjusted to high definition in 1 second and detect.
Native system also is provided with automatic positioning mechanism, according to the orientation tool in the vision-based detection instrument, with product orientation to be measured to normal place.
Native system also is provided with automatic reject mechanism, according to the testing result of vision-based detection instrument in the detection control unit, with the substandard product automatic rejection.
Native system also is provided with human-computer interaction interface, is used for showing the recognition result of product identification unit, and the vision-based detection result of detection control unit output.
The present invention has the following advantages and beneficial effect compared to existing technology:
The present invention is applicable to the multiple product that detects batch production, the use of this system has sufficient dirigibility, be applicable to the manufacturer of various scales, native system can detect large simultaneously on the same production line according to different examination requirementses, little different parts, system can design nearly 10 mm professional camera specials or above automatic detection different station and moving component and with automatic removing device;
But the present invention's automatic intelligent is identified the product style, identified is to control automatic positioning mechanism by program again behind which product, adjusts the camera position that gathers image with this, detects again;
The present invention can come automatic change detection according to the classification of product is different, the detection of taking pictures to the position of appointment of control camera;
Automatic reject mechanism and detent mechanism have conveniently been realized robotization in the rejecting of detection and location and substandard product, need not manually-operated.
Description of drawings
Fig. 1 is the structural representation that can be used for the Machine Vision Inspecting System of multiple product detection;
Fig. 2 is the operational flowchart that can be used for the machine vision detection method of multiple product detection.
Embodiment
The present invention is described in further detail below in conjunction with embodiment and accompanying drawing, but embodiments of the present invention are not limited to this.
Embodiment
As shown in Figure 1, can be used for the Machine Vision Inspecting System that multiple product detects, comprising:
The normal Product Visual distinguishing characteristics thesaurus of surveying is for the visual difference feature of the various normal survey products that prestore;
Detect the configuration parameter thesaurus, for the corresponding detection configuration parameter of the various normal survey products that prestore;
Vision-based detection instrument thesaurus is for the vision-based detection instrument of the various normal survey products that prestore;
Image acquisition units includes a plurality of cameras that multi-angle is made a video recording;
The product identification unit carries out characteristic matching for the image of the product to be measured that will gather and pre-stored visual difference feature, identifies product to be measured and surveys product for which kind of is normal;
Detection control unit according to the recognition result of product identification unit, is called corresponding vision-based detection instrument, loads the detection configuration parameter to the vision-based detection instrument from detecting the configuration parameter thesaurus, and product to be measured is carried out vision-based detection;
Automatic positioning mechanism, according to the orientation tool in the vision-based detection instrument, with product orientation to be measured to normal place;
Automatic reject mechanism is according to the testing result of vision-based detection instrument in the detection control unit, with the substandard product automatic rejection;
Human-computer interaction interface, for the recognition result that shows the product identification unit, and the vision-based detection result of detection control unit output.
Wherein, camera adopts high speed linear array Charge Coupled Device (CCD) imageing sensor (CCD) camera, can analyze the sharpness of interference image and automatically be adjusted to high definition in 1 second and detect.
As shown in Figure 2, can be used for the machine vision detection method that multiple product detects, the corresponding detection configuration parameter of the visual difference feature of pre-stored various normal survey products, various normal survey products, and the vision-based detection instrument of various normal survey products, this method specifically may further comprise the steps:
A. gather the image of product to be measured, image and pre-stored visual difference feature are carried out characteristic matching, find out the normal survey product with this images match, obviously machine assert that described product to be measured and the normal survey product of finding out are like product;
B. find out the detection configuration parameter corresponding with normal survey product;
C. call the vision-based detection instrument corresponding with the normal survey product of finding out, and load the detection configuration parameter of finding out, then according to the vision-based detection instrument that calls product to be measured is carried out vision-based detection.
The corresponding detection configuration parameter of various normal survey products is vision-based detection content and camera parameter setting.Wherein, the vision-based detection content specifically comprise in the having or not of outward appearance, color and principal character of various normal survey products one or more etc.Camera parameter setting specifically comprises one or more in camera resolution, time shutter and the RGB gain etc.
The vision-based detection instrument of various normal survey products includes orientation tool, testing tool and analyzes the output instrument.Wherein, orientation tool comprises based on the orientation tool of contour feature with based on the orientation tool of unique point; Testing tool comprises dimensional measurement instrument, bar code recognition instrument, color and gray scale detection instrument, character recognition, Region Matching testing tool and profile defect detection tool; Analyze the output instrument and comprise product hierarchy decision means and I/O control tool; But similar tools parallel running, the operation of inhomogeneity instrument serializable, the vision-based detection flow process is formed by these vision-based detection tool combinations, and the parameter of the array mode of these instruments and concrete instrument is also namely carried out pre-stored as detecting configuration parameter as the vision-based detection content.
The vision-based detection tool detection go out product to be measured whether qualified after, if defective, then controlling automatic reject mechanism should reject by underproof product to be measured, defective at same problem point such as a plurality of products to be measured of continuous appearance, then automatically stops to detect and making man-machine response.
Above-described embodiment is the better embodiment of the present invention; but embodiments of the present invention are not restricted to the described embodiments; other any do not deviate from change, the modification done under Spirit Essence of the present invention and the principle, substitutes, combination, simplify; all should be the substitute mode of equivalence, be included within protection scope of the present invention.
Claims (10)
1. can be used for the machine vision detection method that multiple product detects, it is characterized in that, the corresponding detection configuration parameter of the visual difference feature of pre-stored various normal survey products, various normal survey products, and the vision-based detection instrument of various normal survey products, this method specifically may further comprise the steps:
A. gather the image of product to be measured, image and pre-stored visual difference feature are carried out characteristic matching, find out the normal survey product with this images match, wherein, machine assert that described product to be measured and the normal survey product of finding out are like product;
B. find out the detection configuration parameter corresponding with normal survey product;
C. call the vision-based detection instrument corresponding with the normal survey product of finding out, and load the detection configuration parameter of finding out, then according to the vision-based detection instrument that calls product to be measured is carried out vision-based detection.
2. according to claim 1ly can be used for the machine vision detection method that multiple product detects, it is characterized in that:
The corresponding detection configuration parameter of described various normal survey products is vision-based detection content and camera parameter setting.
3. according to claim 2ly can be used for the machine vision detection method that multiple product detects, it is characterized in that:
Described vision-based detection content specifically comprises one or more in the having or not of outward appearance, color and principal character of various normal survey products; Camera parameter setting specifically comprises one or more in camera resolution, time shutter and the RGB gain.
4. according to claim 1ly can be used for the machine vision detection method that multiple product detects, it is characterized in that:
The vision-based detection instrument of described various normal survey products includes orientation tool, testing tool and analyzes the output instrument.
5. according to claim 4ly can be used for the machine vision detection method that multiple product detects, it is characterized in that:
Described orientation tool comprises based on the orientation tool of contour feature with based on the orientation tool of unique point; Testing tool comprises dimensional measurement instrument, bar code recognition instrument, color and gray scale detection instrument, character recognition, Region Matching testing tool and profile defect detection tool; Analyze the output instrument and comprise product hierarchy decision means and I/O control tool; The similar tools parallel running, inhomogeneity instrument serial operation, the vision-based detection flow process is formed by these vision-based detection tool combinations, and the parameter of the array mode of these instruments and concrete instrument is also namely carried out pre-stored as detecting configuration parameter as the vision-based detection content.
6. according to claim 1ly can be used for the machine vision detection method that multiple product detects, it is characterized in that: the vision-based detection tool detection go out product to be measured whether qualified after, if defective, then controlling automatic reject mechanism should reject by underproof product to be measured, defective at same problem point such as a plurality of products to be measured of continuous appearance, then automatically stop to detect and making man-machine response.
7. can be used for the Machine Vision Inspecting System that multiple product detects, it is characterized in that:
Comprise:
The normal Product Visual distinguishing characteristics thesaurus of surveying is for the visual difference feature of the various normal survey products that prestore;
Detect the configuration parameter thesaurus, for the corresponding detection configuration parameter of the various normal survey products that prestore;
Vision-based detection instrument thesaurus is for the vision-based detection instrument of the various normal survey products that prestore;
Image acquisition units includes a plurality of cameras that multi-angle is made a video recording;
The product identification unit carries out characteristic matching for the image of the product to be measured that will gather and pre-stored visual difference feature, identifies product to be measured and surveys product for which kind of is normal;
Detection control unit according to the recognition result of product identification unit, is called corresponding vision-based detection instrument, loads the detection configuration parameter to the vision-based detection instrument from detecting the configuration parameter thesaurus, and product to be measured is carried out vision-based detection.
8. the Machine Vision Inspecting System that can be used for the multiple product detection according to claim 7 is characterized in that: the camera in the described image acquisition units, employing high speed linear array Charge Coupled Device (CCD) image sensor camera.
9. according to claim 7ly can be used for the Machine Vision Inspecting System that multiple product detects, it is characterized in that:
Native system also is provided with:
Automatic positioning mechanism, according to the orientation tool in the vision-based detection instrument, with product orientation to be measured to normal place;
Automatic reject mechanism is according to the testing result of vision-based detection instrument in the detection control unit, with the substandard product automatic rejection.
10. according to claim 7ly can be used for the Machine Vision Inspecting System that multiple product detects, it is characterized in that:
Native system also is provided with human-computer interaction interface, is used for showing the recognition result of product identification unit, and the vision-based detection result of detection control unit output.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201110111714 CN102253048B (en) | 2011-04-29 | 2011-04-29 | Machine vision detection method and system for detection of various products |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201110111714 CN102253048B (en) | 2011-04-29 | 2011-04-29 | Machine vision detection method and system for detection of various products |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102253048A CN102253048A (en) | 2011-11-23 |
| CN102253048B true CN102253048B (en) | 2013-05-29 |
Family
ID=44980438
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201110111714 Expired - Fee Related CN102253048B (en) | 2011-04-29 | 2011-04-29 | Machine vision detection method and system for detection of various products |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102253048B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108106532A (en) * | 2017-11-23 | 2018-06-01 | 重庆椿本智能科技有限公司 | The detection method of notebook vision testing machine |
Families Citing this family (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104048968A (en) * | 2014-06-04 | 2014-09-17 | 上海美迪索科电子科技有限公司 | Industrial processing part automatic defect identification system |
| CN104101608B (en) * | 2014-07-01 | 2017-01-25 | 南京航空航天大学 | Intelligent detecting device for detecting defects of multi-type irregularly shaped product |
| CN105548210B (en) * | 2015-12-31 | 2018-05-08 | 广东工业大学 | The detection method of American Standard power extending line based on machine vision |
| CN105718271A (en) * | 2016-02-15 | 2016-06-29 | 福州觉感视觉软件科技有限公司 | Machine vision intelligent detection system |
| CN106123808B (en) * | 2016-06-14 | 2018-09-14 | 上海贝特威自动化科技有限公司 | A method of it is measured for the deflection of automobile rearview mirror specular angle degree |
| CN106383121B (en) * | 2016-06-22 | 2019-11-05 | 深圳市联君科技股份有限公司 | It is a kind of can adaptive multi-brand visible detection method and system |
| CN106018426A (en) * | 2016-07-20 | 2016-10-12 | 武汉大学 | Printed product quality online detection system |
| CN106289183A (en) * | 2016-08-08 | 2017-01-04 | 中国科学院自动化研究所 | Criticize nozzle suit misloading automatic checkout equipment and method thereof |
| CN106546539A (en) * | 2016-09-19 | 2017-03-29 | 嘉兴科瑞迪医疗器械有限公司 | A kind of automatic blood type analytical instrument intelligent vision scanning system |
| CN106598622A (en) * | 2016-12-22 | 2017-04-26 | 陕西维视数字图像技术有限公司 | Smart vision inspection platform |
| CN106919983B (en) * | 2017-02-20 | 2021-07-27 | 北京小米移动软件有限公司 | Workpiece information processing method, device and system |
| CN107978029A (en) * | 2017-09-11 | 2018-05-01 | 浙江力太科技有限公司 | A kind of method based on stacking apparatus enhancing producing line flexibility |
| CN108109137A (en) * | 2017-12-13 | 2018-06-01 | 重庆越畅汽车科技有限公司 | The Machine Vision Inspecting System and method of vehicle part |
| CN108971025A (en) * | 2018-08-17 | 2018-12-11 | 上海玉嵩机器人技术有限公司 | A kind of visible detection method and vision detection system |
| CN110332992B (en) * | 2019-05-27 | 2021-04-30 | 江西理工大学 | Parameter-adjustable optical detection device and method |
| CN110412046A (en) * | 2019-08-22 | 2019-11-05 | 深圳眼千里科技有限公司 | Automate module A I optical test equipment and operation method |
| CN111389750B (en) * | 2020-04-07 | 2022-04-12 | 苏州瀚德光电科技有限公司 | Vision measurement system and measurement method |
| CN111652868A (en) * | 2020-06-01 | 2020-09-11 | 珠海格力智能装备有限公司 | Method and device for setting vision measurement system and method for measuring product |
| CN112116668B (en) * | 2020-11-23 | 2021-04-06 | 常州微亿智造科技有限公司 | Optical copying method and device for quality inspection and quality inspection equipment |
| CN113109365A (en) * | 2021-04-16 | 2021-07-13 | 中国科学院自动化研究所 | Defect detection system and method suitable for various workpieces |
| CN114273245B (en) * | 2021-11-10 | 2024-09-06 | 上海艾豚科技有限公司 | Continuous mixing detection method and system for various workpieces of automotive interior parts |
| CN114273261B (en) * | 2021-11-10 | 2024-09-10 | 上海艾豚科技有限公司 | Simultaneous detection method and system for multiple workpiece suites of automotive interior parts |
| CN114047195A (en) * | 2021-11-11 | 2022-02-15 | 合肥工业大学智能制造技术研究院 | New energy battery cap defect detection method and system |
| CN116883417B (en) * | 2023-09-08 | 2023-12-05 | 武汉东方骏驰精密制造有限公司 | Workpiece quality inspection method and device based on machine vision |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101040184A (en) * | 2004-09-07 | 2007-09-19 | 彼得罗模型公司 | Apparatus and method for analysis of size, form and angularity and for compositional analysis of mineral and rock particles |
| JP2007293732A (en) * | 2006-04-27 | 2007-11-08 | Hitachi High-Technologies Corp | Inspecting device |
| US7860277B2 (en) * | 2007-04-10 | 2010-12-28 | Bizerba Gmbh & Co. Kg | Food product checking system and method for identifying and grading food products |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030223639A1 (en) * | 2002-03-05 | 2003-12-04 | Vladimir Shlain | Calibration and recognition of materials in technical images using specific and non-specific features |
-
2011
- 2011-04-29 CN CN 201110111714 patent/CN102253048B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101040184A (en) * | 2004-09-07 | 2007-09-19 | 彼得罗模型公司 | Apparatus and method for analysis of size, form and angularity and for compositional analysis of mineral and rock particles |
| JP2007293732A (en) * | 2006-04-27 | 2007-11-08 | Hitachi High-Technologies Corp | Inspecting device |
| US7860277B2 (en) * | 2007-04-10 | 2010-12-28 | Bizerba Gmbh & Co. Kg | Food product checking system and method for identifying and grading food products |
Non-Patent Citations (2)
| Title |
|---|
| 席斌 等.机器视觉测量系统在工业在线检测中的应用.《工业控制计算机》.2005,第18卷(第11期),75-76. |
| 机器视觉测量系统在工业在线检测中的应用;席斌 等;《工业控制计算机》;20051231;第18卷(第11期);75-76 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108106532A (en) * | 2017-11-23 | 2018-06-01 | 重庆椿本智能科技有限公司 | The detection method of notebook vision testing machine |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102253048A (en) | 2011-11-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102253048B (en) | Machine vision detection method and system for detection of various products | |
| TWI603074B (en) | Optical film defect detection method and system thereof | |
| CN106226325B (en) | A kind of seat surface defect detecting system and its method based on machine vision | |
| CN102539443B (en) | Bottle body defect automatic detection method based on machine vision | |
| CN102529019B (en) | Method for mould detection and protection as well as part detection and picking | |
| CN108971025A (en) | A kind of visible detection method and vision detection system | |
| CN111047655A (en) | High-definition camera cloth defect detection method based on convolutional neural network | |
| CN107515481B (en) | Display panel detection method and device | |
| CN103439337A (en) | Automatic detection device and method for apparent defects of piezoelectric ceramic buzzers | |
| CN106383121B (en) | It is a kind of can adaptive multi-brand visible detection method and system | |
| CN104197836A (en) | Vehicle lock assembly size detection method based on machine vision | |
| CN115184359A (en) | Surface defect detection system and method capable of automatically adjusting parameters | |
| CN102353349A (en) | Machine vision based micro-sound film concentricity online testing system and testing method | |
| CN107833843A (en) | The analysis method and analysis system of defect source, defect detecting device | |
| CN108414531A (en) | A kind of fexible film defect detecting device and its detection method based on machine vision | |
| CN110096980A (en) | Character machining identifying system | |
| CN113030102A (en) | Paint surface flaw inspection system based on machine vision | |
| CN113000413A (en) | System, method and terminal for detecting surface defects of synchronizer gear sleeve based on machine vision | |
| CN111426693A (en) | Quality defect detection system and detection method thereof | |
| CN106645185A (en) | Method and device for intelligently detecting surface quality of industrial parts | |
| CN109622404B (en) | Automatic sorting system and method for micro-workpieces based on machine vision | |
| CN112070762A (en) | Mura defect detection method and device for liquid crystal panel, storage medium and terminal | |
| CN114226262A (en) | Flaw detection method, flaw classification method and flaw detection system | |
| CN105844282A (en) | Method for detecting defects of fuel injection nozzle O-Ring through line scanning camera | |
| CN203432920U (en) | Device for automatically detecting apparent defects of piezoelectric ceramic buzzing pieces |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| ASS | Succession or assignment of patent right |
Owner name: JIANG ZESHU Free format text: FORMER OWNER: HUIZHOU JUNYUE TECHNOLOGY CO.,LTD. Effective date: 20131231 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| COR | Change of bibliographic data |
Free format text: CORRECT: ADDRESS; FROM: 516001 HUIZHOU, GUANGDONG PROVINCE TO: 516221 HUIZHOU, GUANGDONG PROVINCE |
|
| TR01 | Transfer of patent right |
Effective date of registration: 20131231 Address after: The town of freshwater house market 516221 Guangdong province Huizhou city Huiyang District No. 3 building 504 room Patentee after: Jiang Zeshu Address before: 516001 Guangdong city of Huizhou province science and Technology Park weatherite Zhongkai high tech two East Road No. 16 room 502-2 Patentee before: Huizhou Junyue Technology Co.,Ltd. |
|
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20130529 Termination date: 20150429 |
|
| EXPY | Termination of patent right or utility model |